doc_mod_indo <- lm(prop_doctors ~ log10(pop)*elec_comp_index + pop_growth + density + div_index + avg_income, data = indonesia_data)
teacher_mod_indo <- lm(teachers_prop ~ log10(pop)*elec_comp_index + pop_growth + density + div_index + avg_income, data = indonesia_data)
comm_mod_indo <- lm(prop_comm_health ~ log10(pop)*elec_comp_index + pop_growth + density + div_index + avg_income, data = indonesia_data)
schools_mod_indo <- lm(schools_prop ~ log10(pop)*elec_comp_index + pop_growth + density + div_index + avg_income, data = indonesia_data)
elec_mod_indo <- lm(prop_govt_electricity ~ log10(pop)*elec_comp_index + pop_growth + density + div_index + avg_income, data = indonesia_data)
water_mod_indo <- lm(prop_water ~ log10(pop)*elec_comp_index + pop_growth + density + div_index + avg_income, data = indonesia_data)

mods_indo <- list("Doctors" = doc_mod_indo, 
                  "Teachers" = teacher_mod_indo, 
                  "Health Centers" = comm_mod_indo, 
                  "Schools" = schools_mod_indo, 
                  "Electricity" = elec_mod_indo, 
                  "Water" = water_mod_indo)

options(scipen = 999)
modelsummary(mods_indo,
             output = "./_4_outputs/table_oa_ii.html",
             coef_omit = "Intercept|pop_growth|density|div_index|avg_income",
             fmt = "%.1f",
             gof_map = c("nobs", "r.squared"),
             coef_rename = c("log10(pop)" = "Population (logged)",
                             "elec_comp_index" = "Partisan Fractionalization",
                             "log10(pop):elec_comp_index" = "Population X Fractionalization"),
             stars = T)
